Many currently used wireless communication systems such as LTE, LTE-Advance, IEEE 802.11n and IEEE 802.11ac continuously sense the state of the wireless channel through well-known signals, or pilot signals, in order to dynamically optimize the transmission rate or improve the robustness of the system. These channel sensing mechanisms are continuously improving and enable self-driven calibration systems and wireless signal pre-compensation and post-compensation techniques, significantly improving the quality of wireless communication.
Measurable variables of wireless channels have also been used for the purpose of localization. One of the most commonly used types of information for this purpose is the wireless signal strength. For example, a positioning method for mobile devices has been developed exploiting received signal strength (RSS) data which is collected from multiple reference devices. Based on a path loss function, the RSS data are then used to estimate the distances between the target and the reference devices.
Another positioning method for mobile devices within the prior art exploits the construction of a mapping between the RSS data and the device location, and stores this mapping as fingerprints. The method then compares the new RSS data with the fingerprints to estimate the location of the target device. Alternatively, a field testing tool referred to as “OmniTester” has been developed which integrates received signal-strength and error-rate testing for wireless networks.
More fine-grained information is available in modern communication systems and several approaches have been proposed in order to improve these systems. For example, a method that provides periodic channel state information (CSI) data has been developed. However, these fine-grained measurements are not only valuable for controlling and optimizing communication networks and links as they can also be used for the purpose of localization of subject.
Existing indoor localization approaches based on wireless channel information (e.g., RSS, CSI) depend on at least one of the following two assumptions. First, the subject(s) localization is achieved by localizing a wireless device (e.g., RFID, phone) carried by the subject(s), i.e., device-based localization. Second, fingerprints are established for the localization, i.e., the localization system needs a site survey to be performed before it can actually localize the subject(s).
However, in many application scenarios, neither of the above two assumptions are true, namely that the user is not carrying an active wireless device or that the site has been surveyed. When either or both of these scenarios then there are no techniques within the prior art that provide for the localization of subject(s) within an indoor environment.
Accordingly, it would be beneficial to provide an indoor localization system which is device-free and requires no fingerprinting before system deployment.
Other aspects and features of the present invention will become apparent to those ordinarily skilled in the art upon review of the following description of specific embodiments of the invention in conjunction with the accompanying figures.